Physical Sciences and Mathematics Commons^™

Risk Prediction With Genomic Data, Bharati Jadhav

Theses

Genome wide association study (GWAS) is widely used with various machine learning algorithms to predict disease risk. This thesis investigates this widely used approach of GWAS using Single Nucleotide Polymorphism (SNP) genotype data and a novel approach of disease risk prediction with whole exome sequencing data, namely Whole Exome Wide Association Study (WEWAS). It further applies a discriminating machine learning algorithm, namely a Support Vector Machine (SVM) with different Kernel functions. For this study, only SNPs generated using genotyping technology, which focuses more on common variants, are used initially for disease prediction. Later, the whole exome data generated using Next …